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Democratization of Artificial Intelligence for the Future of Humanity

Artificial intelligence (AI) stands out as a transformational technology of the digital age. Its practical applications are growing very rapidly. One of the chief reasons AI applications are attaining prominence, is in its design to learn continuously, from real-world use and experience, and its capability to improve its performance. Les mer
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Paperback
Legg i
Vår pris: 1012,-

(Paperback) Fri frakt!
Leveringstid: Sendes innen 7 virkedager
På grunn av Brexit-tilpasninger og tiltak for å begrense covid-19 kan det dessverre oppstå forsinket levering.

Om boka

Artificial intelligence (AI) stands out as a transformational technology of the digital age. Its practical applications are growing very rapidly. One of the chief reasons AI applications are attaining prominence, is in its design to learn continuously, from real-world use and experience, and its capability to improve its performance. It is no wonder that the applications of AI span from complex high-technology equipment manufacturing to personalized exclusive recommendations to end-users. Many deployments of AI software, given its continuous learning need, require computation platforms that are resource intense, and have sustained connectivity and perpetual power through central electrical grid.


In order to harvest the benefits of AI revolution to all of humanity, traditional AI software development paradigms must be upgraded to function effectively in environments that have resource constraints, small form factor computational devices with limited power, devices with intermittent or no connectivity and/or powered by non-perpetual source or battery power.


The aim this book is to prepare current and future software engineering teams with the skills and tools to fully utilize AI capabilities in resource-constrained devices. The book introduces essential AI concepts from the perspectives of full-scale software development with emphasis on creating niche Blue Ocean small form factored computational environment products.

Fakta

Innholdsfortegnelse

SECTION I - INTRODUCTION TO ARTIFICIAL INTELLIGENCE AND FRAMEWORKS


Introduction


What is AI?


AI Epoch's: Waves of Compute


AI Hype Cycle - Current and Emerging Technologies


AI - End-To-End (E2E) Process - Turning Data into Actionable Insights


Microsoft Azure - AI E2E Platform


AI Development Operations (DevOps) Loop for Data Science


AI -Performance and Computational Notations


AI for Greater Good - Solving Humanity and Societal Challenges


References





Standard Processes and Frameworks


Digital Transformation


Digital Feedback Loop


Insights Value Chain


The CRISP-DM Process


Building Blocks of AI - Major Components of AI


AI Reference Architectures


References


SECTION II - DATA SOURCES AND ENGINEERING TOOLS


Data - Call for Democratization


Call for Action


The Last Mile - Constrained Compute Devices AND "AI Chasm"


References





Machine Learning Frameworks and Device Engineering


Machine Learning Device Deployments


xRC Modeling: Model Accuracy-Connectivity-Hardware (MCH) Framework


Circular Buffers


AI Democratization - "Crossing the Chasm"


References





Device Software and Hardware Engineering Tools


Software Engineering Tools


Hardware and Engineering Tools


Libraries


References


SECTION III - MODEL DEVELOPMENT AND DEPLOYMENT


Supervised Models


Decision Trees


XGBoost


Random Forrest


Naive Bayesian


Linear Regression


Kalman Filter


References





Unsupervised Models


Hierarchical Clustering


K-Means Clustering


References


SECTION IV - DEMOCRATIZATION AND FUTURE OF AI


National Strategies


National Technology Strategies for Serving People


The United Nations AI Technology Strategy


The role of the UN


AI in the Hands of People


References





Future


Democratization of Artificial Intelligence for the Future of Humanity


Dedication


Acknowledgement


Preface





Appendix





Index

Om forfatteren

Chandrasekar Vuppalapati graduated from San Jose State University Masters Program, specializing Software Engineering, and completed his Master of Business Administration from Santa Clara University, Santa Clara, California, USA. He is a Software IT Executive and Entrepreneur with diverse experience in Software Technologies, Enterprise Software Architectures, Cloud Computing, Data Analytics, Internet of Things (IoT), and Software Product & Program Management. Chandra has held engineering architectures and product leadership roles at Microsoft, GE Healthcare, Cisco Systems, St. Jude Medical, and Lucent Technologies, a Bell Laboratories Company. He teaches Software Engineering, Large Scale Analytics, Data Science, Mobile Technologies, Cloud Technologies, and Web & Data Mining for Masters program in San Jose State University. Chandra has also held market research, strategy and technology architecture advisory roles in Cisco Systems, Lam Research and performed Principal Investigator role for Valley School of Nursing where he connected Nursing Educators & Students with Virtual Reality technologies. He has authored several international conference papers and published book on Building Enterprise IoT Applications. Chandra has served as Chair in numerous technology and advanced computing conferences such as: IEEE Oxford, UK, IEEE Big Data Services 2017, San Francisco USA, Future of Information and Communication Conference 2018, Singapore and Intelligent Human Systems Integration (IHSI) 2020, Modena, Italy.